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The lithologic profile of pyroclastic rock is based on the sedimentary environment of multiple sources, which has the characteristics of lithologic grain variation of continental clastic rock and the characteristics of rock composition from different sources. Based on the physical characteristics of the logging project, the curve value contains two aspects of rock particle size and composition information, so it is necessary to judge the transition lithology with thin thickness and complex composition according to the change relationship between upper and lower lithology. According to the variation characteristics of pyroclastic rock in the logging response of Hailaer Basin, a continuous lithologic profile variation model is established, which effectively improves the identification accuracy of transitional lithology in the lithologic profile.

In this article, we start from the samples and the kernel principal component contribution rate adaptive point of view. Our aim is to research that how to choose the initial parameters of the mixed kernel function in comprehensive evaluation of KPCA. To some extent, it will overcome the shortcomings that the kernel function parameter is difficult to determine, and it provides an effective method that KPCA applies to determine the kernel function initial parameter of the multi-indexes comprehensive evaluation. We believe that it will be more widely applied to feature extraction with its advantages appear in specific issues, and makes the evaluation method more and more scientific and effective.